Learning analytics (LA) has become a critical field for transforming educational practices through data-driven insights. This study presents a comprehensive bibliometric analysis of LA research in higher education from 2013 to 2023, utilizing the Scientific Procedures and Rationales for Systematic Literature Review (SPAR-4-SLR) approach. By…

Technology-enhanced learning supported by virtual learning environments (VLEs) facilitates tutors and students. VLE platforms contain a wealth of information that can be used to mine insight regarding students' learning behaviour and relationships between behaviour and academic performance, as well as to model data-driven decision-making. This…

Educational data mining involves the application of data mining techniques to student activity. However, in the context of computer programming, many data mining techniques can not be applied because they require vector-shaped input, whereas computer programs have the form of syntax trees. In this paper, we present ast2vec, a neural network that…

Accounting for complex interactions between contextual variables and learners' individual differences in aptitudes and background requires building the means to connect and access learner data at large scales, across time, and in multiple contexts. This paper describes the ASU Learning@Scale (L@S) project to develop a digital learning network…

Traditional assessment in international sports communication is often fragmented and subjective, limiting timely, learner-centered feedback. This study presents a curriculum framework enhanced by generative artificial intelligence, coupled with a deep learning (DL) model for instructional effectiveness assessment in international sports…